A Monte-Carlo Approach for Tracking Mobile Personnel

In this paper, we propose a Monte-Carlo method based on the particle filter framework to track footfall locations generated by mobile personnel using seismic arrays. While the particle proposal function follows a simple bootstrap approach, the novelty in our algorithm comes from a unique weighting strategy that takes into account the sparse nature of the seismic footfall signal and is robust against missed detections and clutter which could appear in the form of other impulsive sources or other walkers. Our weighting strategy automatically makes use of the wavefront shape, either planar or circular, and assigns weights in x-y space. Data association is built into the system, eliminating the need to explicitly associate the received footfall impulses with different walkers. Hence our algorithm is ideal for tracking multiple mobile personnel. We also demonstrate the fusion of our system with range information available by means of radar. Fusion with radar improves x-y tracking when range resolution is lost due to a large distance between the target and the seismic array leading to planar wavefronts.